We propose a new method, VASA, based on variable subsample aggregation of model predictions for equity returns using a large-dimensional set of factors. To demonstrate the effectiveness, robustness, and dimension reduction power of VASA, we perform a comparative analysis between state-of-the-art...

Technical trading rules are widely used by practitioners to forecast the U.S. equity premium. I decompose technical indicators into components with frequency-specific information, showing that the predictive power comes from medium-frequency variation in buy and sell signals, without much...

We assess the ability of an information aggregation mechanism that operates in the over-the-counter market for financial derivatives to reduce valuation uncertainty among market participants. The analysis is based on a unique dataset of price estimates for S&P 500 index options that major...

We study the effect of a huge sports sentiment shock, unrelated to economic conditions or government actions, on stock market outcomes. After Brazil's 7-1 humiliating defeat to Germany in the 2014 World Cup, which is likely to be one of the largest sports sentiment shocks ever, the stock market...

We develop an Arbitrage Pricing Theory framework extension to study the pricing of squared returns/volatilities. We analyze the interplay between factors at the return level and those in idiosyncratic variances. We confirm the presence of a common idiosyncratic variance factor, but do not find...

We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm that the simple combination of individual predictors is superior. However, sophisticated models improve dramatically...

This study develops an empirical algorithm within which the incentive for signaling of private information in course of IPOs is implemented as a conditional, as opposed to an unconditional incentive. Suppose high quality issuers of IPOs signal private information, and suppose presence of cohorts...

We estimate corporate bond portfolios using numerous asset-specific characteristics. Our portfolio weights accommodate a large cross-section and allow for a flexible management of turnover and liquidity. A portfolio tilted toward higher maturity, credit risk, coupon, momentum, and size...

Approximate factor models and their extensions are widely used in economic analysis and forecasting due to their ability to extracting useful information from a large number of relevant variables. In these models, candidate predictors are typically subject to some common components. In this...

We examine the properties and forecast performance of multiplicative volatility specifications that belong to the class of GARCH-MIDAS models suggested in Engle et al. (2013). In those models volatility is decomposed into a short-term GARCH component and a long-term component that is driven by...